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communities. You will be introduced to a multi-sector international community committed to more equitable systems. We prioritize a balanced and family-friendly work-life relationship, offering options
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avenues will be pursued: advancing our toroidal anvil capabilities to extend the maximum achievable pressure ranges; and depositing designed electrical circuits to create advanced multi-modal experiments
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) Department Huck Institutes of the Life Sciences Location University Park, PA, with periodic international travel Funding Bill & Melinda Gates Foundation and NIH (multi-year) Duration Annual appointment
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compatibility guidelines and biologically based pest management approaches aligned with New York State IPM priorities and the phase-out of neonicotinoid seed treatments. Anticipated Division of Time Experimental
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multi-omic sequencing, network biology, and machine learning to identify actionable biomarkers and therapeutic vulnerabilities. The successful candidate will work at the interface of computational
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 14 days ago
ongoing externally funded clinical research projects within the ITR. Design, implement, and oversee clinical trials, including emergency department-based, multi-site studies. Develop and manage
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, etc.) and quantitative data analysis. Excellent written and oral communication skills. Ability to work effectively in a collaborative, multi-institutional team environment. Ability to model Argonne’s
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
for model refinement. Perform multi-scale simulations (e.g. DFT / atomistic / phase-field simulations) to train AI/ML models. Conduct scientific research on ferroelectrics and/or 2D memristive materials
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in multiscale and multifidelity simulation techniques (ab initio methods at different fidelity, machine learning tight-binding, machine learning force fields, phase-field modeling, and/or kinetic monte
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team and contribute to IDEAS (Intelligent Data Exploration Assistant for Science), a multi-year research effort focused on developing AI-powered visualization systems that enable interactive, human-in